Research on Identification Method of Anonymous Fake Reviews in E-commerce
Abstract: In this paper, a new
method has been proposed for identifying anonymous fake reviews generated by
click farmers in E-commerce and improves the identification rates. Anonymous
fake reviews are different from the gunuine reviews. They could be
distinguished based on the credibility of users, the average daily number of
evaluations, the content similarity, and the degree of word overlapping. The proposed
method takes into account these 5 features to calculate the fake reviews
content by constructing multivariate linear regression model, Experiments show
that this prelimilnary work performed well in identifying fake reviews in
Chinese E-commerce website. The extracted features are also useful to identifying
the fake reviews when the reviewer’s identification is not accessable.
Author: Lizhen Liu
Journal Code: jptkomputergg160276
